User personalization has an important impact on a wide range of activities from travel time, food selection, to targeted messaging. The ability to improve the accuracy of decision engines is largely dependent on the ability to characterize the end user accurately.
Traditional decision engines utilize static user profiles with often large amounts of parametric data as a means of increasing accuracy of decision engines.
Prior art of US Patent Pending 20100004997 is based on an unknown user profile, and uses location including the attempted distinction between a work and home location to determine an anticipated user profile.
The invention being described utilizes a known user profile to dynamically change the mode and thus the sub-segment of the user to more accurately create context for the specific activity and/or location in which the user (again having a known user profile, i.e., gender, age, etc.) is engaged in. Furthermore, the invention recognizes that a specific user having a known user profile engages in a wide range of activities that have fundamentally different behaviors and characteristics that range from limited to a complete absence of similarities to the known user profile.
The combined limitations of static user profiles and large amounts of parametric data leads to inaccuracies and complex interaction with decision engines requiring longer processing times and/or more powerful processors.